Learning OWA operator weights from data

Abstract

We investigate the issue of obtaining the weights associated with the ordered weighted operator (OWA) aggregation in the situation when we have observed data on the arguments and the aggregated value. This provides a procedure to learn the decision maker's level of confidence from previous decisions. We next introduce a family of OWA operators called exponential OWA operators.<>